Tool to dump and compare internal activation tensors (#7976)

python/sglang/srt/debug_utils/dumper.py

@@ -0,0 +1,108 @@
+import os
+import time
+from pathlib import Path
+from typing import Optional
+
+import torch
+import torch.distributed as dist
+
+
+class _Dumper:
+    """Utility to dump tensors, which can be useful when comparison checking models.
+
+    Example usage:
+    dumper.on_forward_pass_start()
+    dumper.dump("layer_start__hidden_states", hidden_states, layer_id=self.layer_id)
+
+    Import from non-SGLang system:
+    ```
+    import sys
+    sys.path.append("/YOUR_PATH/sglang/python/sglang/srt/debug_utils")
+    from dumper import dumper
+    ```
+
+    Related: `sglang.srt.debug_utils.dump_comparator` for dump comparison
+    """
+
+    def __init__(self):
+        # Do not import `sglang` to make this file standalone
+        self._enable = bool(int(os.environ.get("SGLANG_DUMPER_ENABLE", "1")))
+        self._base_dir = Path(os.environ.get("SGLANG_DUMPER_DIR", "/tmp"))
+        self._enable_write_file = bool(
+            int(os.environ.get("SGLANG_DUMPER_WRITE_FILE", "1"))
+        )
+        self._partial_name: Optional[str] = None
+        self._dump_index = 0
+        self._forward_pass_id = 0
+
+    def on_forward_pass_start(self):
+        self._forward_pass_id += 1
+        print(
+            f"[Dumper] [{time.time()}] on_forward_pass_start id={self._forward_pass_id}"
+        )
+
+    def dump(self, name, value, **kwargs):
+        if not self._enable:
+            return
+
+        assert (
+            self._forward_pass_id >= 1
+        ), "Do you forget to call `dumper.on_forward_pass_start()`?"
+        self._dump_index += 1
+
+        if self._partial_name is None:
+            self._partial_name = _get_partial_name()
+
+        rank = dist.get_rank()
+        full_kwargs = dict(
+            forward_pass_id=self._forward_pass_id,
+            rank=rank,
+            name=name,
+            dump_index=self._dump_index,
+            **kwargs,
+        )
+        full_filename = "___".join(f"{k}={v}" for k, v in full_kwargs.items()) + ".pt"
+        path = self._base_dir / f"sglang_dump_{self._partial_name}" / full_filename
+
+        sample_value = get_truncated_value(value)
+
+        print(
+            f"[Dumper] [{rank}, {time.time()}] {path} "
+            f"type={type(value)} "
+            f"shape={value.shape if isinstance(value, torch.Tensor) else None} "
+            f"dtype={value.dtype if isinstance(value, torch.Tensor) else None} "
+            f"sample_value={sample_value}"
+        )
+
+        if self._enable_write_file:
+            path.parent.mkdir(parents=True, exist_ok=True)
+            torch.save(value, str(path))
+
+
+def _get_partial_name():
+    rank = dist.get_rank()
+    object_list = [str(time.time()) if rank == 0 else None]
+    dist.broadcast_object_list(object_list, device="cuda")
+    return object_list[0]
+
+
+def get_truncated_value(value):
+    if value is None:
+        return None
+
+    if isinstance(value, tuple):
+        return [get_truncated_value(x) for x in value]
+
+    if not isinstance(value, torch.Tensor):
+        return None
+
+    if value.numel() < 200:
+        return value
+
+    slices = [
+        slice(0, 5) if dim_size > 200 else slice(None) for dim_size in value.shape
+    ]
+    return value[tuple(slices)]
+
+
+dumper = _Dumper()